Over the last four decades there has been a world-wide increase in the incidence of melanoma. Although adequate sun protection has been identified as the first step toward preventing the occurrence of melanoma, early diagnosis and excision is the key to the survival of the many individuals who will still develop the disease.
A range of techniques have been developed to assess pigmented lesions. With the most common of these, dermatoscopy, a hand held microscope is used to visualise morphological characteristics at the dermo-epidermal junction. Clinicians then attempt to diagnose the presence of melanoma by analysing the lesion by colour, pattern and specific morphological features.
In addition to conventional dermatoscopy, a number of new techniques recently been developed by Astron Clinica Limited based on research undertaken at the University of Birmingham. These techniques are described in WO 00/75637 and WO 98/22023. The techniques use a quantitative understanding of the way light is absorbed and scattered within skin to produce maps of melanin, blood and collagen.
The original research undertaken at the University of Birmingham argued that the Kubelka-Munk theory is sufficient to model light transport within skin. If exact scattering and absorption coefficients can be specified, then the Kubelka-Munk theory can be applied at each wavelength in the visible range and corresponding remittance spectrum obtained. This predicted spectrum, which will determine the colour of the skin, will be dependent on the histological characteristics of the tissue. Three parameters capture most of the variation in remitted spectra from healthy skin. These three parameters are concentration of epidermal melanin, concentration of blood and thickness of the papillary dermal layer (collagen thickness).
Using the RGB response curves for a digital camera together with a model of the scattering and absorption characteristics of the skin, it is possible to calculate the set of image values which would be measured by a digital camera when skin with a known remittance spectrum S(λ) is illuminated with light of known spectral characteristics I(λ). This is done by calculating the convolution integral for each channel, given as,ired=∫I(λ)S(λ)R(λ)dλ, igreen=∫I(λ)S(λ)G(λ)dλ, iblue=∫I(λ)S(λ)B(λ)dλwhere R(λ), G(λ) and B(λ) are the response curves for the red, green and blue channels and ired, iblue and igreen are the corresponding values recorded by the camera at a given pixel
By ranging through all potential combination of melanin, blood and collagen, it is possible to generate all possible spectra and therefore all possible sets of image values which would be measured by a digital camera. Once this information has been obtained a link can be established between image values and histological parameter values. This link can be expressed as a mathematical function.
An image, acquired using a digital camera, consists of a large number of very small pixels, each of which have a set of image values, (ired, igreen and iblue). By applying the mathematical function, linking these image values to histological parameter values, it is possible to obtain values for melanin, blood and collagen at every pixel within an image of skin. This information can then be displayed in the form of histological parametric map. The SIAscope®, developed by Astron Clinica Limited, relies on a specially adapted camera which is able to capture 4 channels of image data. As well the normal RGB channels, it also acquires an image in the infra-red region of the spectrum. With this additional information, it is possible to produce an additional parametric map of dermal melanin.
Determining measurements of epidermal melanin, blood, collagen and dermal melanin directly from measurements of remitted light S(λ) requires that a suspect lesion is illuminated with light of known spectral characteristics I(λ). Using such an approach it is therefore necessary to follow a strict calibration procedure where lighting levels are strictly controlled. This limits the use of such an approach to analyzing small areas of skin as once larger areas of tissue are imaged, over which the surface geometry of the imaged tissue varies, calibration is no longer possible and analysis becomes inaccurate. The maps produced by such a technique have been shown to be of great value to clinicians in their diagnosis of melanoma. However, due to the required calibration procedures, it is typically only possible to produce a map of dermal melanin over a small area of skin, currently 15 mm diameter.
Although effective, prior art techniques thus currently require detailed individual analysis of every suspect lesion on a given patient and thus rely on the clinician being able to quickly identify all potentially dangerous lesions. While this is straight-forward for the majority of patients, some individuals present with large numbers of skin lesions. In this situation it would be useful to have some tool which would be able to automatically identify all lesions requiring a detailed inspection.
In order to overcome the problems arising due to strict calibration requirements an alternative technique has been developed. This is described in detail in Astron Clinica's prior patent application WO 04/010862. The technique relies on a mathematical function linking histological parameters with ratios of image values, rather than the actual image values. Determining measurements from ratios of image values removes the need for calibration. This can be demonstrated mathematically by considering the case where illumination which can be described byI(λ)=α1Ī(λ),where α1 is a wavelength independent scaling factor which captures changes in illumination intensity and Ī(λ) captures the wavelength dependence of the incident light. The amount of light remitted from a tissue will depend on both the histological characteristics of the tissue and the angle of the tissue to the camera. The remitted spectrum can therefore be expressed asS(λ)=α2 S(λ)where α2 is a wavelength independent scale factor which depends on the angle of the tissue to the camera and S(λ) is the remitted spectrum which depends on the histology of the imaged tissue. Ratios of image values are now given as,
            r      greenOverRed        =                  α        ⁢                  ∫                                                    I                _                            ⁡                              (                λ                )                                      ⁢                          S              ⁡                              (                λ                )                                      ⁢                          G              ⁡                              (                λ                )                                      ⁢                          ⅆ              λ                                                  α        ⁢                  ∫                                                    I                _                            ⁡                              (                λ                )                                      ⁢                          S              ⁡                              (                λ                )                                      ⁢                          R              ⁡                              (                λ                )                                      ⁢                          ⅆ              λ                                            ,          ⁢            r      blueOverRed        =                            α          ⁢                      ∫                                                            I                  _                                ⁡                                  (                  λ                  )                                            ⁢                              S                ⁡                                  (                  λ                  )                                            ⁢                              B                ⁡                                  (                  λ                  )                                            ⁢                              ⅆ                λ                                                              α          ⁢                      ∫                                                            I                  _                                ⁡                                  (                  λ                  )                                            ⁢                              S                ⁡                                  (                  λ                  )                                            ⁢                              R                ⁡                                  (                  λ                  )                                            ⁢                              ⅆ                λ                                                        .      where α=α1α2. The factor α, which captures all variation due to illumination changes and changes in surface geometry of the images tissue, will cancel out in each of the equations above leaving only wavelength dependent terms. Thus the image ratios can be seen to be independent of both illumination and surface geometry.
Variation in skin histology can then be thought of in terms of a parameter space and spectra are computed, using the Kubelka-Munk model, which correspond to each point with parameter space. By applying the above equations it is then possible to calculate the two image ratios rgreenOverRed and rblueOverRed which correspond to a given spectra. Using the above technique, measurements of blood and melanin concentrations can be made without having to control for surface geometry and lighting conditions.
Although very effective for characterising normal skin, the described technique in WO 04/010862 is however limited to obtaining measurements of melanin and blood concentrations. The technique is not suitable for obtaining measurements of collagen as changes in collagen have an equal effect at every wavelength and therefore no effect on a ratio of two spectral measures. Further disclosed techniques are unable to determine whether melanin is present only within the epidermis of the skin or whether melanin has penetrated into the dermis. To be of use as a screening tool it must be possible to measure dermal melanin as if information showing the presence of dermal melanin could be displayed this would alert the clinician to any suspicious lesions
An alternative system which assists with the identification of suspect lesions is therefore desirable.